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References

    1. 1)
      • 1. Xu, W., Yu, J.: ‘A novel approach to information fusion in multi-source datasets: a granular computing viewpoint’, Inf. Sci., 2017, 378, pp. 410423.
    2. 2)
      • 25. Raghavan, U.N., Albert, R., Kumara, S.: ‘Near linear time algorithm to detect community structures in large-scale networks’, Phys. Rev. E, 2007, 76, p. 036106.
    3. 3)
      • 26. Sun, P.G., Gao, L., Shan Han, S.: ‘Identification of overlapping and non-overlapping community structure by fuzzy clustering in complex networks’, Inf. Sci., 2011, 181, (6), pp. 10601071.
    4. 4)
      • 6. Xu, W., Li, M., Wang, X.: ‘Information fusion based on information entropy in fuzzy multi-source incomplete information system’, Int. J. Fuzzy Syst., 2017, 19, (4), pp. 12001216.
    5. 5)
      • 4. Xu, W., Guo, Y.: ‘Generalized multigranulation double-quantitative decision-theoretic rough set’, Knowl.-Based Syst., 2016, 105, (1), pp. 190205.
    6. 6)
      • 14. Salton, G.: ‘Automatic text processing: the transformation, analysis, and retrieval of information by computer’ (Addison-Wesley, Academic Press, New York, 1989), pp. 123145.
    7. 7)
      • 18. Zhang, Z.Y.: ‘Community structure detection in complex networks with partial background information’, Europhys. Lett., 2013, 101, (4), p. 48005.
    8. 8)
      • 12. Ma, X., Gao, L., Yong, X., et al: ‘Semi-supervised clustering algorithm for community detection in complex networks’, Physica A, 2010, 389, (1), pp. 187197.
    9. 9)
      • 24. Lusseau, D., Schneider, K., Boisseau, O., et al: ‘The bottlenose dolphin community of doubtful sound features a large proportion of long-lasting associations’, Behav. Ecol. Sociobiol., 2003, 54, (4), pp. 396405.
    10. 10)
      • 16. Newman, M.E.J.: ‘Modularity and community structure in networks’, Proc. Natl. Acad. Sci., 2006, 103, (23), pp. 85778582.
    11. 11)
      • 22. Ng, A.Y., Jordan, M.I., Weiss, Y.: ‘On spectral clustering: analysis and an algorithm’. Proc. Advances in Neural Information Processing Systems, New York, USA, 2001, pp. 849856.
    12. 12)
      • 19. Zhang, Z.Y., Sun, K.D., Wang, S.Q.: ‘Enhanced community structure detection in complex networks with partial background information’, Sci. Rep., 2013, 3, p. 3241.
    13. 13)
      • 17. Ver Steeg, G., Galstyan, A., Allahverdyan, A.E.: ‘Statistical mechanics of semi-supervised clustering in sparse graphs’, J. Stat. Mech. Theory Exp., 2011, 2011, (8), p. P08009.
    14. 14)
      • 7. Rosvall, M., Bergstrom, C.T.: ‘Maps of random walks on complex networks reveal community structure’, Proc. Natl. Acad. Sci., 2008, 105, (4), pp. 11181123.
    15. 15)
      • 8. Sang, B., Guo, Y., Shi, D., et al: ‘Decision-theoretic rough set model of multi-source decision systems’, Int. J. Mach. Learn. Cybern., 2018, 9, pp. 19411954.
    16. 16)
      • 11. Liu, Z., Li, P., Zheng, Y., et al: ‘Community detection by affinity propagation’. Technical report, 2008.
    17. 17)
      • 5. Xu, W., Li, W.: ‘Granular computing approach to two-way learning based on formal concept analysis in fuzzy datasets’, IEEE Trans. Cybern., 2016, 46, (2), pp. 366379.
    18. 18)
      • 9. Chai, B., Wang, J., Yu, J.: ‘A parameter selection method of the deterministic anti-annealing algorithm for network exploring’, Neurocomputing, 2017, 226, pp. 192199.
    19. 19)
      • 13. Salton, G., Mcgill, M.J.: ‘Introduction to modern information retrieval’ (McGraw-Hill Book Company, Academic Press, New York, 1983), pp. 4589.
    20. 20)
      • 2. Jiang, Y.: ‘Community detection in complex networks’, Beijing Jiaotong University, Beijing, 2014, pp. 3233.
    21. 21)
      • 20. Cheng, J., Leng, M., Li, L., et al: ‘Active semi-supervised community detection based on must-link and cannot-link constraints’, PLOS ONE, 2014, 9, (10), pp. 118.
    22. 22)
      • 21. Zachary, W.: ‘An information flow model for conflict and fission in small groups’, J. Anthropol. Res., 1977, 33, pp. 452473.
    23. 23)
      • 15. Hamers, L., Hemeryck, Y., Herweyers, G., et al: ‘Similarity measures in scientometric research: the Jaccard index versus Salton's cosine formula’, Inf. Process. Manage., 1989, 25, (3), pp. 315318.
    24. 24)
      • 3. Karthik, S., Aggarwal, C.C., Jaideep, S., et al: ‘Community detection with prior knowledge’. SIAM Data Mining, Dalian, Liaoning, China, 2013.
    25. 25)
      • 10. Girvan, M., Newman, M.E.J.: ‘Community structure in social and biological networks’, Proc. Natl. Acad. Sci., 2002, 99, (12), pp. 78217826.
    26. 26)
      • 23. Newman, M.E.J.: ‘Fast algorithm for detecting community structure in networks’, Phys. Rev. E, 2004, 69, p. 066133.
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